Equitable Medicine Requires Fair Payment

Paternalistic fears of “undue inducement” damage equity of biomedical research

If healthcare is to be the right of all Americans, it must serve all Americans well. To provide healthcare that serves the needs of diverse clinical populations, we need to end the functional exclusion of minority populations from clinical trials. While many approaches are necessary to solve this problem, only one is de facto banned: offering patients fair compensation for joining a clinical trial.

Undue Inducement versus Fair Payment

FDA guidance requires payment to not be so high that it constitutes “undue inducement.” They argue that clinical trial participation entails risks, and it would be irresponsible to offer payments that are so large that a patient can no longer assess those risks with a clear head. Therefore, clinical trials are allowed to cover costs for transport and time, but very little more.

From a purely theoretical standpoint, undue inducement is not obviously worse than underpayment. To start, this guidance is paternalistic in its asymmetrical application to patients versus medical practitioners; I have never heard somebody argue that surgeons are coerced into performing risky operations by their high salary. Furthermore, the entire premise of undue inducement acknowledges that we are not compensating patients for the risks they are choosing to take. In this light, I do not see the ethical necessity of preventing fair-market compensation for a participant’s enrollment.

The empirical evidence is much more damning; limiting trial compensation excludes low-income participants from enrollment. Multiple studies have found that, in hypothetical trial scenarios, increasing payments do not alter risk perception. An actual trial that randomized the amount of compensation for low-risk studies found that higher payment did not cause patients to accept more risk, confirmed not only in the data but also through qualitative interviews. In other words, we lack sufficient evidence to conclude that undue inducement is anything beyond a theoretical concern.

Given that Black and Hispanic Americans are of low income at disproportionately higher rates, if fair payment causes low-income patients to enroll more frequently in clinical trials, then we should expect fair payment to create more diverse clinical trial populations. To be fair, there is no conclusive causal evidence that fair payment will affect patient diversity one way or the other. Yet still, even this is the result of undue inducement guidance—if it is functionally illegal to pay patients more, then there is no way to assess whether paying patients more will produce more diverse populations. However, attempting fair payment may be particularly helpful for diseases that cause significant financial burden.

Fair payment could alleviate financial burden in cancer trials

Cancer entails incredible financial strain, intensifying the barriers of clinical trial enrollment for low-income patients. In cancer trials, patients with a household income of less than $50k have 32% lower odds of participation. 48% of patients who participated in cancer trials had out-of-pocket costs of over $1,000, and Black and Latino patients were more likely to report high unanticipated costs.

It is likely that these financial barriers contribute to the lack of Black and Hispanic enrollment in cancer clinical trials. According to a review of all Phase I oncology trials performed in the US and published in 2019, only 7% of patients are Black and less than 3% are Latino. For context, 15% of people with cancer are Black and 13% are Latino. This discrepancy in trial participation is in large part due to differences in enrollment rates. In 280 American cancer clinics from 2017-2022, only a little more than 4% of Black and Hispanic cancer patients enrolled in clinical trials compared to 7% of white patients. Unfortunately, this type of underrepresentation is the norm in clinical trials. Observing all US trials from 2000-2020, the majority report no ethnicity enrollment data at all. The studies that do report this data routinely underrepresent minority populations.

Drugs we have now are likely inequitable in ways we cannot quantify

Mechanistically, inequitably sampled research produces inequitable medical outcomes due to differences in drug metabolism across populations. Those Phase I oncology trials are used to calibrate the dosage for the safe administration of a drug. Given that patients with different genetic ancestry produce different enzymes for drug metabolism, calibrating dosage for one population is not guaranteed to translate to all populations. For drugs as potent as those used for chemotherapy, a poorly calibrated dose could either fail to produce a clinical effect or induce dangerous levels of toxicity. For all drugs approved from 2008-2013, one in five reported differences in mechanism, safety, dosage, or efficacy between ethnic groups.

A more fundamental issue: inequitable studies are statistically unlikely to even detect differences when non-white patients constitute a rounding-error of each study. Those one-in-five drugs are only the drugs that produced differences we could measure in under-representative clinical trials; it is likely that many more drugs have differences that aren’t detected due to insufficient sample size.

To be clear, the primary driver for the difference in clinical outcomes for Black patients with cancer in America comes down to insurance status. Most studies suggest that the core problem comes down to how Black patients are less likely to have insurance that will cover high-quality cancer prevention, detection, and treatment, resulting in diagnosis at later stages that are more difficult to treat. Equal access to treatment would be an incredible boon for medical equity in the United States—this is a key motivation for universal healthcare.

Inequitable sampling bias personalized medicine towards European populations

However, universal access to the clinical methods we already have is insufficient, we must aspire towards universal access to all future medical advancement. To better treat complex diseases like cancer, many new drugs are personalized to the individual biology of the patients. Scientists can use tools like genetic risk scores to categorize patients into different sub-classes that will respond better to one drug or another. If we had large samples across ethnic groups, this could be an incredibly useful tool to provide the right medication to the right patients.

Unfortunately, genetic risk scores defined on patients of European ancestry fail to transfer to patients of other ancestries. In 2019, genetic risk scores trained on primarily-European subjects had one-fifth the predictive accuracy for patients of African descent. The clearest evidence for the benefit of diverse clinical populations comes from the VA Million Veteran Program study designed to identify the relationship between genes and disease across populations. One-third of this study’s participants were of non-European ancestry compared to the mere 12% present in all similar studies combined. This study found 1608 genetic risk loci and one-third of all causal variants were only identifiable through the inclusion of non-European populations. In other words, while there is a great deal of shared genetic architecture between all people, many variants which cause disease come from rare mutations that are only detectable by sampling the entire diversity of our society.

By providing fair compensation for low-income patients that are disproportionately non-white, we could make a step towards closing this evidentiary gap. Underrepresentation of non-white patients in clinical trials is a complex issue that fair payment alone will not solve, but it may help boost enrollment for diseases that induce strong financial burdens like cancer. If ensuring medical equity is to remain a political goal, we cannot rely on universal healthcare alone. We must also seriously engage with the clinical trial reform that is necessary to root out systemic medical racism and deliver the advances of biomedical science to all.